ArticleBiomolecules2020
High-Throughput Identification of Adapters in Single-Read Sequencing Data.
Article in Biomolecules, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 14 citations in OpenAlex.
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- Genome-wide selective sweep analysis in high-altitude Changthangi goats reveals candidate genes for pashmina fiber production.Mammalian genome : official journal of the International Mammalian Genome Society · 2025Article
- Charting the equine miRNA landscape: An integrated pipeline and browser for annotating, quantifying, and visualizing expression.PLoS genetics · 2025Article
- Integrating genomic, transcriptomic, and phenotypic information to explore drug resistance in Mycobacterium tuberculosis sub-lineage 4.2.2.2.Journal of applied microbiology · 2025Article
- FindAdapt: A python package for fast and accurate adapter detection in small RNA sequencing.PLoS computational biology · 2024Article
- Integration of soil microbiology and metabolomics to elucidate the mechanism of the accelerated infestation of tobacco by the root-knot nematode.Frontiers in microbiology · 2024Article
- Discovering a novel glycosyltransferase geneFrontiers in microbiology · 2024Article
- mtR_find: A Parallel Processing Tool to Identify and Annotate RNAs Derived from the Mitochondrial Genome.International journal of molecular sciences · 2023Article
- An unusual ectopic thymoma clonal evolution analysis: A case report.Open life sciences · 2023Article
- Expression profiles of tRNA-derived fragments and their potential roles in lung adenocarcinoma.Annals of translational medicine · 2022Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Sequencing datasets available in public repositories are already high in number, and their growth is exponential. Raw sequencing data files constitute a substantial portion of these data, and they need to be pre-processed for any downstream analyses. The removal of adapter sequences is the first essential step. Tools available for the automated detection of adapters in single-read sequencing protocol datasets have certain limitations. To explore these datasets, one needs to retrieve the information on adapter sequences from the methods sections of appropriate research articles. This can be time-consuming in metadata analyses. Moreover, not all research articles provide the information on adapter sequences. We have developed adapt_find, a tool that automates the process of adapter sequences identification in raw single-read sequencing datasets. We have verified adapt_find through testing a number of publicly available datasets. adapt_find secures a robust, reliable and high-throughput process across different sequencing technologies and various adapter designs. It does not need prior knowledge of the adapter sequences. We also produced associated tools: random_mer, for the detection of random N bases either on one or both termini of the reads, and fastqc_parser, for consolidating the results from FASTQC outputs. Together, this is a valuable tool set for metadata analyses on multiple sequencing datasets.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.